| description abstract | Data-driven social equity assessments of infrastructure performance are essential for reducing inequity and for institutionalizing community stakeholder considerations in infrastructure asset management programs. We expand upon literature at the intersection of engineering management and social impact, which has focused on the engineering workforce or the stakeholders of individual projects, to inform equity assessments of overarching programs and their outcomes. We conducted a social equity assessment of the National Bridge Inventory (NBI) component condition ratings by comparing the contribution of established bridge deterioration modeling variables to community demographics surrounding the bridge. To do this, we extend existing ordered probit regression modeling approaches of bridge component condition ratings to a national dataset that spatially matches NBI bridge coordinate data to US Census Bureau tracts to append indicators for income, race, ethnicity, and disadvantaged communities. We found that bridges located in lower-income tracts, tracts identified as disadvantaged communities by the Climate and Economic Screening Tool (CEJST), and tracts with a majority of Black or African American individuals are more likely to be in poor condition. At least on an associative basis, we find that bridge condition is not equitably distributed across communities in the United States, even when controlling for differences in deterioration due to age, traffic type, traffic volume, bridge materials, waterways, and climate. This study suggests that racial equity should be an added component (beyond economic measures of inequity) that informs bridge maintenance program funding and project prioritization to ensure greater equity in our bridge system. | |
